AIP-C01 Question #3: Real Exam Question with Answer & Explanation

Question

A specialty coffee company has a mobile app that generates personalized coffee roast profiles by using Amazon Bedrock with a three-stage prompt chain. The prompt chain converts user inputs into structured metadata, retrieves relevant logs for coffee roasts, and generates a personalized roast recommendation for each customer. Users in multiple AWS Regions report inconsistent roast recommendations for identical inputs, slow inference during the retrieval step, and unsafe recommendations such as brewing at excessively high temperatures. The company must improve the stability of outputs for repeated inputs. The company must also improve app performance and the safety of the app's outputs. The updated solution must ensure 99.5% output consistency for identical inputs and achieve inference latency of less than 1 second. The solution must also block unsafe or hallucinated recommendations by using validated safety controls. Which solution will meet these requirements?

Options

• ADeploy Amazon Bedrock with provisioned throughput to stabilize inference latency. Apply
• BUse Amazon Bedrock Agents to manage chaining. Log model inputs and outputs to Amazon
• CCache prompt results in Amazon ElastiCache. Use AWS Lambda functions to pre-process
• DUse Amazon Kendra to improve roast log retrieval accuracy. Store normalized prompt metadata